Bayesian methods for image super-resolution

Computer Journal

Volumn 52, Issue 1, 2009, Pages 101-113

  Pickup, Lyndsey C ^a   Capel, David P ^b   Roberts, S J Stephen J ^a   Zisserman, Andrew ^a  

^a Department of Engineering Science ^*  (United Kingdom)

^b 2D3 Ltd

Author keywords

Bayesian; Image prior; Image registration; Super resolution

Indexed keywords

IMAGE REGISTRATION; OPTICAL RESOLVING POWER;

BAYESIAN; BAYESIAN METHODS; COMPUTATIONAL BOTTLENECKS; GEOMETRIC AND PHOTOMETRIC REGISTRATIONS; HIGH-RESOLUTION IMAGES; IMAGE POINTS; IMAGE PRIOR; MARGINALIZATION; NOVEL METHODS; PRIOR DISTRIBUTIONS; REALISTIC IMAGES; SUPER-RESOLUTION; SYNTHETIC DATA SETS;

BAYESIAN NETWORKS;

EID: 60649088498     PISSN: 00104620     EISSN: 14602067     Source Type: Journal    
DOI: 10.1093/comjnl/bxm091     Document Type: Article

References (23)

1. Irani, M. and Peleg, S. (1990) Super resolution from image sequences. Proc. Int. Conf. Pattern Recognition, vol. 2, pp. 115-120.
2. Salient, Stills. http://www.salientstills.com/.
3. Hardie, R.C., Barnard, K.J. and Armstrong, E.E. (1997) Joint map registration and high-resolution image estimation using a sequence of undersampled images. IEEE Trans. Image Process., 6, 1621-1633.
4. Robinson, D. and Milanfar, P. (2004) Fundamental performance limits in image registration. IEEE Trans. Image Process., 13, 1185-1199.
5. Tipping, M.E. and Bishop, C.M. (2003) Bayesian image super-resolution. In Becker, S., Thrun, S. and Obermayer, K. (eds) Advances in Nueral Information Processing Systems 15. MIT Press, Cambridge, MA.
6. Baker, S. and Kanade, T. (2002) Limits on superresolution and how to break them. IEEE Trans. Pattern Anal. Mach. Intell., 24, 1167-1183.
7. Capel, D. (2004) Image Mosaicing and Super-resolution (Distinguished Dissertations). Springer, ISBN: 1852337710.
8. Elad, M. and Feuer, A. (1999) Super-resolution reconstruction of image sequences. IEEE Trans. Pattern Anal. Mach. Intell., 21, 817-834.
9. Elad, M. and Hel-Or, Y. (2001) A fast super-resolution reconstruction algorithm for pure translational motion and common space invariant blur. IEEE Trans. Image Process., 10, 1187-93.
10. Farsiu, S., Elad, M. and Milanfar, P. (2006) A practical approach to super-resolution. Proc. SPIE: Visual Communications and Image Processing, San-Jose.
11. Nguyen, N., Milanfar, P. and Golub, G. (2001) Efficient generalized cross-validation with applications to parametric image restoration and resolution enhancement. IEEE Trans. Image Process., 10, 1299-1308.
12. Wang, Q., Tang, X. and Shum, H. (2005) Patch based blind image super resolution. Proc. 10th Int. Conf. Computer Vision, Beijing, China, pp. 709-716.
13. Pickup, L.C., Roberts, S.J. and Zisserman, A. (2006) Optimizing and learning for super-resolution. In Chantler, M.J., Trucco, E. and Fisher, R.B. (eds) Proc. British Machine Vision Conf., vol. 3, pp. 439-448. Edinburgh, UK.
14. Schultz, R.R. and Stevenson, R.L. (1994) A Bayesian approach to image expansion for improved definition. IEEE Trans. Image Process., 3, 233-242.
15. Pickup, L.C., Capel, D.P., Roberts, S.J. and Zisserman, A. (2006) Bayesian image super-resolution, continued. In Schölkopf, B., Platt, J. and Hoffman, T. (eds) Advances in Neural Information Processing Systems 19, December, pp. 1089-1096. MIT Press, Cambridge, MA.
16. Borman, S. (2004) Topics in multiframe superresolution restoration. PhD Thesis, University of Notre Dame Notre Dame, Indiana.
17. Fergus, R., Singh, B., Hertzmann, A., Roweis, S.T. and Freeman, W. (2006) Removing camera shake from a single photograph. ACM Trans. Graphics, SIGGRAPH 2006 Conf. Proc., Boston, MA, 25, PP. 787-794.
18. Molina, R., Vega, M., Abad, J. and Katsaggelos, A.K. (2003) Parameter estimation in bayesian high-resolution image reconstruction with multisensors. IEEE Trans. Image Process., 12, 1655-1667.
19. Pickup, L.C. (2007) Gradient derivation for parametermarginalizing image super-resolution. Technical report. University of Oxford.
20. Irani, M. and Peleg, S. (1991) Improving resolution by image registration. Graph. Models Image Process., 53, 231-239.
21. Hartley, R.I. and Zisserman, A. (2004) Multiple View Geometry in Computer Vision (2nd edn) Cambridge University Press. ISBN: 0521540518.
22. Kundur, D. and Hatzinakos, D. (1996) Blind image deconvolution. IEEE Signal Process. Mag., 13, 43-46.
23. Nabney, I. (2002) Netlab Algorithms for Pattern Recognition. Springer.